Struct OneVsRestWrapper

pub struct OneVsRestWrapper<T> { /* private fields */ }

Wraps simple two-class classifiers to implement one-vs-rest strategies.

Implementations

impl<T: Clone> OneVsRestWrapper<T>

pub fn new(base_model: T) -> OneVsRestWrapper<T>

pub fn models(&self) -> &Vec<T>

pub fn class_labels(&self) -> &Vec<f32>

Trait Implementations

impl<'de, T> Deserialize<'de> for OneVsRestWrapper<T>

where T: Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync> ParallelPredict<&'a Array> for OneVsRestWrapper<T>

fn decision_function_parallel( &self, X: &'a Array, num_threads: usize, ) -> Result<Array, &'static str>

fn predict_parallel( &self, X: &'a Array, num_threads: usize, ) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone + Sync> ParallelPredict<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn decision_function_parallel( &self, X: &'a SparseColumnArray, num_threads: usize, ) -> Result<Array, &'static str>

fn predict_parallel( &self, X: &'a SparseColumnArray, num_threads: usize, ) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone + Sync> ParallelPredict<&'a SparseRowArray> for OneVsRestWrapper<T>

fn decision_function_parallel( &self, X: &'a SparseRowArray, num_threads: usize, ) -> Result<Array, &'static str>

fn predict_parallel( &self, X: &'a SparseRowArray, num_threads: usize, ) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a Array> + Clone + Sync + Send> ParallelSupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit_parallel( &mut self, X: &'a Array, y: &Array, num_threads: usize, ) -> Result<(), &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone + Sync + Send> ParallelSupervisedModel<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn fit_parallel( &mut self, X: &'a SparseColumnArray, y: &Array, num_threads: usize, ) -> Result<(), &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone + Sync + Send> ParallelSupervisedModel<&'a SparseRowArray> for OneVsRestWrapper<T>

fn fit_parallel( &mut self, X: &'a SparseRowArray, y: &Array, num_threads: usize, ) -> Result<(), &'static str>

impl<T> Serialize for OneVsRestWrapper<T>

where T: Serialize,

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<'a, T: SupervisedModel<&'a Array> + Clone> SupervisedModel<&'a Array> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a Array, y: &Array) -> Result<(), &'static str>

fn decision_function(&self, X: &'a Array) -> Result<Array, &'static str>

fn predict(&self, X: &'a Array) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseColumnArray> + Clone> SupervisedModel<&'a SparseColumnArray> for OneVsRestWrapper<T>

fn fit( &mut self, X: &'a SparseColumnArray, y: &Array, ) -> Result<(), &'static str>

fn decision_function( &self, X: &'a SparseColumnArray, ) -> Result<Array, &'static str>

fn predict(&self, X: &'a SparseColumnArray) -> Result<Array, &'static str>

impl<'a, T: SupervisedModel<&'a SparseRowArray> + Clone> SupervisedModel<&'a SparseRowArray> for OneVsRestWrapper<T>

fn fit(&mut self, X: &'a SparseRowArray, y: &Array) -> Result<(), &'static str>

fn decision_function( &self, X: &'a SparseRowArray, ) -> Result<Array, &'static str>

fn predict(&self, X: &'a SparseRowArray) -> Result<Array, &'static str>